IT Governance
IT governance is a framework that ensures your organization’s IT infrastructure supports and enables the achievement of its corporate strategies and objectives. The full definition can be found in IT Governance: A Pocket Guide by Alan Calder. IT governance framework is a type of framework that defines the ways and methods through which an organization can implement, manage and monitor IT governance within an organization The official IT governance standard is ISO/IEC 38500:2015. It sets out a straightforward framework for the board’s governance of information and communications technology and is a key resource for IT governance professionals everywhere in the world.
Curriculum
Understanding Big Data and Hadoop
- Introduction to Big Data & Big Data ChallengesÂ
- Limitations & Solutions of Big Data Architecture
- Hadoop & its Features
- Hadoop Ecosystem
- Hadoop 2.x Core ComponentsÂ
- Hadoop Storage: HDFS (Hadoop Distributed File System)
- Hadoop Processing: MapReduce Framework
- Different Hadoop Distributions
Hadoop Architecture and HDFS
- Hadoop 2.x Cluster ArchitectureÂ
- Federation and High Availability ArchitectureÂ
- Typical Production Hadoop Cluster
- Hadoop Cluster Modes
- Common Hadoop Shell CommandsÂ
- Hadoop 2.x Configuration Files
- Single Node Cluster & Multi-Node Cluster set up
- Basic Hadoop Administration
Hadoop MapReduce Framework
- Traditional way vs MapReduce way
- Why MapReduceÂ
- YARN Components
- YARN Architecture
- YARN MapReduce Application Execution Flow
- YARN Workflow
- Anatomy of MapReduce ProgramÂ
- Input Splits, Relation between Input Splits and HDFS Blocks
- MapReduce: Combiner & Partitioner
- Demo of Health Care Dataset
- Demo of Weather Dataset
Advanced Hadoop MapReduce
- Counters
- Distributed Cache
- MRunit
- Reduce JoinÂ
- Custom Input FormatÂ
- Sequence Input Format
- XML file Parsing using MapReduce
Apache Pig
- Introduction to Apache PigÂ
- MapReduce vs Pig
- Pig Components & Pig Execution
- Pig Data Types & Data Models in Pig
- Pig Latin ProgramsÂ
- Shell and Utility Commands
- Pig UDF & Pig Streaming
- Testing Pig scripts with Punit
- Aviation use-case in PIG
- Pig Demo of Healthcare Dataset
Apache Hive
- Introduction to Apache HiveÂ
- Hive vs Pig
- Hive Architecture and ComponentsÂ
- Hive Metastore
- Limitations of Hive
- Comparison with Traditional Database
- Hive Data Types and Data Models
- Hive Partition
- Hive Bucketing
- Hive Tables (Managed Tables and External Tables)
- Importing Data
- Querying Data & Managing Outputs
- Hive Script & Hive UDF
- Retail use case in Hive
- Hive Demo on Healthcare Dataset
Advanced Apache Hive and HBase
- Hive QL: Joining Tables, Dynamic PartitioningÂ
- Custom MapReduce Scripts
- Hive Indexes and viewsÂ
- Hive Query Optimizers
- Hive Thrift Server
- Hive UDFÂ
- HBase v/s RDBMS
- HBase Components
- HBase ArchitectureÂ
- HBase Run Modes
- HBase Configuration
- HBase Cluster Deployment
Advanced Apache HBase
- HBase Data ModelÂ
- HBase Shell
- HBase Client API
- Hive Data Loading Techniques
- Apache Zookeeper Introduction
- ZooKeeper Data Model
- Zookeeper Service
- HBase Bulk LoadingÂ
- Getting and Inserting Data
- HBase Filters
Processing Distributed Data with Apache Spark
- What is SparkÂ
- Spark Ecosystem
- Spark ComponentsÂ
- What is ScalaÂ
- Why Scala
- SparkContext
- Spark RDD
Oozie and Hadoop Project
- OozieÂ
- Oozie Components
- Oozie Workflow
- Scheduling Jobs with Oozie Scheduler
- Demo of Oozie Workflow
- Oozie CoordinatorÂ
- Oozie Commands
- Oozie Web Console
- Oozie for MapReduce
- Combining flow of MapReduce Jobs
- Hive in Oozie
- Hadoop Project Demo
- Hadoop Talend Integration
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Syllabus
Foundation
Execution and Implementation
Management
Big Data Solutions
Analytics and Big Data
Cloud Technologies
Target Audience
Best suited to Information Technology professionals who possess intermediate to advanced programming, systems administration or relational database skills and are looking to move into the area of Big Data. These include
- Software Engineersli
- Application Developers
- IT Architects
- System Administrators
- The course can also be of benefit to other professionals, e.g. business analysts, market/data researchers, etc. who possess strong information Technology skills and have a deep interest in Big Data analytics and the benefits it can bring to an organization.